%b Model:
%br
Source:
%a{:href=>model.source, :target=>"external"}
  = model.source
%br
= "Algorithm:\tLAZAR"
%br
- model.classification? ? type = "Classification" : type = "Regression"
= "Type:\t"
= type
%br
- training_dataset = OpenTox::Dataset.find model.training_dataset.id
= "Training dataset:\t"
= training_dataset.source.split("/").last
%br
= "Training compounds:\t"
= training_dataset.compounds.size

%p
%b Validation (repeated):
%div.row{:id=>"validations#{model.id}", :style=>"background-color:#f5f5f5;"}
  - model.crossvalidations.each do |crossvalidation|
    %span.col-xs-4.col-sm-4.col-md-4.col-lg-4
      - cv = OpenTox::CrossValidation.find crossvalidation.id
      = "Num folds:\t"
      = cv.folds
      %br
      = "Num instances:\t"
      = cv.nr_instances
      %br
      = "Num unpredicted"
      = cv.nr_unpredicted
      - if model.classification? 
        %br
        = "Accuracy:\t"
        = cv.accuracy.round(3) if cv.accuracy
        %br
        = "Weighted Accuracy:\t"
        = cv.weighted_accuracy.round(3) if cv.weighted_accuracy
        %br
        = "True positive rate:\t"
        = cv.true_rate["active"].round(3) if cv.true_rate["active"]
        %br
        = "True negative rate:\t"
        = cv.true_rate["inactive"].round(3) if cv.true_rate["inactive"]
        %br 
        = "Positive predictive value:\t"
        = cv.predictivity["active"].round(3) if cv.predictivity["active"]
        %br
        = "Negative predictive value:\t"
        = cv.predictivity["inactive"].round(3) if cv.predictivity["inactive"]
        %p
        %b Confusion Matrix:
        %table.table.table-condensed.table-borderless{:style=>"width:20%;"}
          %tbody
            %tr
              %td
              %td
              %td 
                %b actual
              %td
              %td
            %tr
              %td
              %td
              %td active
              %td inactive
              -#%td total
            %tr
              %td 
                %b predicted
              %td active
              %td 
                =cv.confusion_matrix[0][0]
              %td 
                =cv.confusion_matrix[0][1]
              -#%td 
                =cv.confusion_matrix[0][0]+cv.confusion_matrix[0][1]
            %tr
              %td
              %td inactive
              %td 
                =cv.confusion_matrix[1][0]
              %td 
                =cv.confusion_matrix[1][1]
              -#%td 
                =cv.confusion_matrix[1][0]+cv.confusion_matrix[1][1]
            -#%tr
              %td
              %td total
              %td
                =cv.confusion_matrix[0][0]+cv.confusion_matrix[1][0]
              %td
                =cv.confusion_matrix[0][1]+cv.confusion_matrix[1][1]
              %td
                -#= "Confusion Matrix:\t"
                -#= cv.confusion_matrix
      - if model.regression?
        %br
        = "Root mean squared error:\t"
        = cv.rmse.round(3) if cv.rmse
        %br
        = "Weighted root mean squared error:\t"
        = cv.weighted_rmse.round(3) if cv.weighted_rmse
        %br
        = "Mean absolute error:\t"
        = cv.mae.round(3) if cv.mae
        %br
        = "Weighted mean absolute error:\t"
        = cv.weighted_mae.round(3) if cv.weighted_mae
        %br 
        = "R square:\t"
        = cv.r_squared.round(3) if cv.r_squared
        /%br
        /= "Correlation plot"
        /= cv.correlation_plot
        /%br
        /= "Confidence plot:"
        /= cv.confidence_plot
%br